Data Factory

Accelerate data integration

Integrate data silos with Azure Data Factory, a service built for all data integration needs and skill levels. Easily construct ETL and ELT processes code-free within the intuitive visual environment, or write your own code. Visually integrate data sources using more than 80 natively built and maintenance-free connectors at no added cost. Focus on your data – the serverless integration service does the rest.

No code or maintenance required to build hybrid ETL and ELT pipelines within the Data Factory visual environment

Improve productivity with shorter time to market

Develop simple and comprehensive ETL and ELT processes without coding or maintenance. Ingest, move, prepare, transform and process your data in a few clicks, and complete your data modelling within the accessible visual environment. The managed Apache Spark™ service in Azure Databricks takes care of code generation and maintenance.

Transfer data using prebuilt connectors

Access the ever-expanding portfolio of more than 80 prebuilt connectors – including Azure data services, on-premises data sources, Amazon S3 and Redshift, and Google BigQuery – at no additional cost. Data Factory provides efficient and resilient data transfer by using the full capacity of underlying network bandwidth, delivering up to 1.5 GB/s throughput.

Integrate data cost-effectively

Integrate your data using a serverless tool with no infrastructure to manage. Only pay for what you use, and scale out with elastic capabilities as your data grows. Transform data with speed and scalability using the Apache Spark engine in Azure Databricks. Integrate expanded datasets from external organisations. Use Azure Data Share to accept new datasets into your Azure analytics environment, then use Data Factory to integrate them into your pipelines to prepare, transform and enrich your data to generate insights.

Work the way you want

Data Factory provides a single hybrid data integration service for all skill levels. Use the visual interface or write your own code in Python, .NET or ARM to build pipelines. Put your choice of processing services into managed data pipelines, or insert custom code as a processing step in any pipeline.

Get continuous integration and delivery (CI/CD)

Continuously monitor and manage pipeline performance alongside applications from a single console with Azure Monitor. Integrate your DevOps processes using the built-in support for pipeline monitoring. If you prefer a less programmatic approach, use the built-in visual monitoring tools and alerts.

Trusted, global cloud presence

Access Data Factory in more than 25 countries/regions. The data-movement service is available globally to ensure data compliance, efficiency and reduced network egress costs.

LUMEDX uses Data Factory to produce insights in a fraction of the time it previously took. The California-based company provides information systems that consolidate the images and data cardiologists use to plan patient care.

Frequently asked questions about Data Factory

We guarantee that we will successfully process requests to perform operations against Data Factory resources at least 99.9 per cent of the time. We also guarantee that all activity runs will be initiated within four minutes of their scheduled execution times at least 99.9 per cent of the time. Read the full Data Factory service-level agreement (SLA).

Integration runtime (IR) is the compute infrastructure that Data Factory uses to provide data integration capabilities across network environments. IR moves data between the source and destination data stores while providing support for built-in connectors, format conversion, column mapping and scalable data transfer. IR provides the capability to natively execute SSIS packages for dispatch activities and natively executes SSIS packages in a managed Azure compute environment. It supports dispatching and monitoring of transformation activities running on several compute services. For more information, see integration runtime in Data Factory.